Are We There Yet? Impact of the First International Standard for Cytomegalovirus DNA on the Harmonization of Results Reported on Plasma Samples
Bibliographic record
Abstract
BACKGROUND: Interassay harmonization of cytomegalovirus (CMV) DNA measurement is important for infection management. Uncertainty exists regarding the result harmonization achievable in patient plasma samples using quantitative polymerase chain reaction (qPCR) assays with calibrators now traceable to the First World Health Organization International Standard (IS) for CMV DNA. METHOD: Serial dilutions of the IS and a blinded panel of 40 genotyped CMV DNA-positive pooled plasma samples and 10 negative plasma samples were tested by 6 laboratories using 10 qPCR assays calibrated to the IS. Each clinical sample was constructed using plasma from a single unique transplant recipient. RESULTS: The variance for individual CMV DNA-positive samples was greater for clinical samples (median, 1.50 [range, 1.22-2.82] log10 IU/mL) than for IS dilutions (median, 0.94 [range, 0.69-1.35] log10 IU/mL) (P < .001); 58.9% of all clinical sample results and 93.6% of IS dilution results fell within ±0.5 log10 IU/mL of the mean viral load of each sample. Result variability was not impacted by either genotype or quantitative levels of CMV DNA. Testing procedure differences can significantly influence results, even when analyte-specific reagents are identical. For clinical samples, all assays demonstrated result bias (P < .008). Assays with amplicon sizes ≤86 bp had significantly higher results compared to assays with larger amplicon sizes (≥105 bp) (P < .001). CONCLUSIONS: The variability in CMV DNA results reported on individual samples has been reduced by the IS, but ongoing clinically relevant variability persists, preventing meaningful interassay result comparison.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.263 | 0.319 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".